Background: Psychological complications are frequent in type 1 diabetes (T1D) but they might be difficult to distinguish one from the other in clinical practice. Our objective was to study the distinguishing characteristics, overlaps and their use in the literature between three concepts of T1D: depression, diabetes distress (DD) and diabetes burnout (DB). Methods: A scoping review (PRISMA guidelines) performed in three databases (PubMed/MEDLINE, PsycInfo, Web of Science) with the keywords: T1D, depression, diabetes and burnout, from January 1990 to June 2021. We selected original studies with participants with T1D, which reported depression, DD, or DB. We extracted information about the concepts, their sub-concepts and screening tools. Findings: Of the 4763 studies identified, 201 studies were included in the study. Seventy-three percent, 57% and 45% of sub-concepts do not overlap in depression, DD, and DB, respectively. We observed overlap between depression (27%)/DD (27%) and between DD (20%)/DB (50%). Interpretation: A number of sub-concepts distinguish depression and DD. Overlaps between concepts suggest that a more precise definition is still lacking. DB is still a relatively new concept and more research is needed to better understand how it can present itself differently, in order to personalize care in comparison to those having DD.

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BACKGROUND Despite significant research done with youth experiencing homelessness (YEH), few studies have examined movement patterns and digital habits in this population. Examining these digital behaviors may provide useful data to design new intervention models for YEH. OBJECTIVE The objective of this study was to explore patterns of mobile phone Wi-Fi usage and GPS location movement among YEH. Additionally, we further examined the relationship between usage and location as correlated with mental health symptoms. METHODS A total of 35 adolescent and young adult participants were recruited from the general community of YEH in a mobile intervention study that included installing a sensor data acquisition app (Purple Robot) for up to six months. Of these participants, 19 had sufficient data to conduct analyses. At baseline, participants completed self-reported measures for depression (PHQ-9) and PTSD (PCL-5). Behavioral features were developed and extracted from phone location and usage data. RESULTS Almost all participants (95%) used private networks for most of their non-cellular connectivity. Greater Wi-Fi usage was associated with higher PCL-5 score (P = 0.006). Location entropy was also found to be associated with both PCL-5 (P = 007) and PHQ-9 (P = .045) scores. CONCLUSIONS Location and Wi-Fi usage both demonstrated associations with PTSD symptoms while only location was associated with depression symptom severity. While further research needs to be done establish the consistency of these findings, they suggest that the digital patterns of YEH offer insights that could be used to tailor digital interventions.